Rapid determination of tea polyphenols content in Qingzhuan tea based on near infrared spectroscopy in conjunction with three different PLS algorithms

Abstract

Tea polyphenols are one of the most important ingredients in Qingzhuan tea. Usually, a chemical method is used to determine tea polyphenols content, but it was time-consuming and laborious. This paper attempted to use near infrared spectroscopy (NIRS) technology combined with three partial least squares methods to predict tea polyphenols content quickly and nondestructively. The partial least squares (PLS), synergy interval PLS (siPLS) and genetic algorithm based PLS (gaPLS) were used to establish prediction models, the performance of the final model was showed by root mean square error of prediction (RMSEP) and determination coefficient (Rp 2 ) in prediction set. The best spectral preprocessing method was multivariate scattering correction (MSC); the RMSEP and R p 2 of PLS model were 0.145% and 0.8974, respectively; the siPLS model was established with four spectral regions (4377.6 cm -1 -4751.7 cm -1 , 4755.6 cm -1 -5129.7 cm -1 , 6262.7 cm -1 -6633.9 cm -1 and 7386 cm -1 -7756.3 cm -1 ), whose RMSEP and R p 2 were 0.0652% and 0.9235, respectively; the gaPLS model was established with 36 spectra dada points and showed the best performance (RMSEP=0.0624%, Rp 2 =0.9769) compared with the PLS and si-PLS models. Therefore, the application of near infrared technology combined with the gaPLS method could predict tea polyphenols content in Qingzhuan tea more accurately and rapidly.

Tracing models for checking beef adulterated with pig blood by Fourier transform near-infrared paired with linear and nonlinear chemometrics

“…While the numbers of hidden neurons was fixed, the unique optimal solution could be achieved by ELM. For its extreme learning speed and good generalization performance, ELM has attracted the attention of food researchers (Wang et al, 2020). The calculation process of the ELM is described by Equations 1 to 10 below.…”

“…Therefore, while FT-NIR technology is utilized for food measurements, chemometrics models must be constructed and optimized for goals of quality-based classification or prediction of quality indicators. The FT-NIR spectroscopy coupled with the optimized model constitutes a unique analytical strategy for the specific targets and objects (Fodor et al, 2020;Wang et al, 2022b). Although many FT-NIR-based techniques could be standardized, they still worthy of further research to construct reliable and efficient chemometrics models for precise target measurement.…”

Rapid and non-destructive determination of tea polyphenols content in Chongzhou new loquat tea lines based on near infrared spectroscopy

“…2) In order to effectively remove a large amount of background information and noise information in the spectra and improve the signal-to-noise ratio when modeling, spectral free preprocessing (None), standard normal variable (SNV), multiple scatter correction (MSC), first derivative (FD), second derivative (SD) and their combination spectral preprocessing methods were used to denoise the original spectrum (Wang et al, 2022b), and the best spectral preprocessing method was selected; 3) The biPLS method was used to divide all the pretreated spectral data equally into 10-22 spectral subintervals, and the partial least squares model was established with the n-1 remaining spectral subintervals through the method of leaving-one. When the root mean square error of cross validation (RMSECV) was the lowest, the spectral intervals obtained were the selected characteristic spectral subintervals reflecting the tea polyphenols content in Chongzhou new loquat tea lines samples.…”